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Navigation for UAV Pair-Supported Relaying in Unknown IoT Systems with Deep Reinforcement Learning
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Unmanned aerial vehicles(UAVs)have recently been regarded as a promising technology in In-ternet of things(IoT).UAVs functioned as intermediate relay nodes are capable of establishing uninterrupted and high-quality communication links between remotely de-ployed IoT devices and the destination.Multiple UAVs are required to be deployed due to their limited onboard energy.We study a UAV pair-supported relaying in un-known IoT systems,which consists of transmitter and re-ceiver.Our goal is that transmitter gathers the data from each device then transfers the information to receiver,and receiver finally transmits the information to the des-tination,while meeting the constraint that the amount of information received from each device reaches a certain threshold.This is an optimization problem with highly coupled variables,such as trajectories of transmitter and receiver.On account of no prior knowledge of the envir-onment,a dueling double deep Q network(dueling DDQN)algorithm is proposed to solve the problem.Whether it is in the phase of transmitter's receiving in-formation or the phase of transmitter's forwarding in-formation to receiver,the effectiveness and superiority of the proposed algorithm is demonstrated by extensive sim-ulationsin in comparison to some base schemes under dif-ferent scenarios.
Unmanned aerial vehicles(UAVs)In-ternet of things(IoT)UAV pairRelayingDueling DDQN
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